Human Motion Tracking by Registering an Articulated Surface to 3-D Points and Normals

Radu Horaud 1 Matti Niskanen 1 Guillaume Dewaele 2 Edmond Boyer 1
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : We address the problem of human motion tracking by registering a surface to 3-D data. We propose a method that iteratively computes two things: Maximum likelihood estimates for both the kinematic and free-motion parameters of a kinematic human-body representation, as well as probabilities that the data are assigned either to a body part, or to an outlier cluster. We introduce a new metric between observed points and normals on one side, and a parameterized surface on the other side, the latter being defined as a blending over a set of ellipsoids. We claim that this metric is well suited when one deals with either visual-hull or visual-shape observations. We illustrate the method by tracking human motions using sparse visual-shape data (3-D surface points and normals) gathered from imperfect silhouettes.
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Journal articles
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https://hal.inria.fr/inria-00446898
Contributor : Radu Horaud <>
Submitted on : Wednesday, January 13, 2010 - 4:05:17 PM
Last modification on : Thursday, April 19, 2018 - 2:54:03 PM
Long-term archiving on : Thursday, June 17, 2010 - 10:44:09 PM

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Radu Horaud, Matti Niskanen, Guillaume Dewaele, Edmond Boyer. Human Motion Tracking by Registering an Articulated Surface to 3-D Points and Normals. IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2009, 31 (1), pp.158-163. ⟨10.1109/TPAMI.2008.108⟩. ⟨inria-00446898⟩

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